Computational Drug Repurposing for Endometriosis Using Single-Cell RNA Sequencing — Patent Specification

Glen Charles Ritschel, Claude
2026 · doi:10.5281/zenodo.20030663 · W7160069991
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Using single-cell RNA sequencing of endometrial biopsies, this patent specification identifies top drug candidates for endometriosis repurposing through computational analysis of differentially expressed genes and chemical library screening.

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This patent specification details a computational approach to drug repurposing for endometriosis by applying single-cell RNA sequencing analysis to the GSE179640 dataset comprising 47,957 cells from 32 biopsies. The researchers utilized a standardized pipeline involving batch correction and clustering to identify differentially expressed genes, subsequently screening over twenty thousand drug candidates against these targets. The analysis highlighted specific top candidates such as CHEMBL5653589 and lestaurtinib based on their predicted efficacy scores derived from the genomic data. This paper is centrally about endometriosis — specifically the identification of potential therapeutic agents through computational modeling of single-cell transcriptomic profiles.

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Abstract

Patent specification for a computational drug repurposing analysis of endometriosis using single-cell RNA sequencing. Applied a standardized scRNA-seq pipeline (scVI batch correction, Leiden clustering, Wilcoxon DE, ChEMBL screening) to GSE179640 (47,957 endometrial biopsy cells, 32 samples). Identified 500 significant DE genes and scored 20,510 drug candidates; 20,117 confirmed novel via PubChem. Top candidates: CHEMBL5653589 (score 190.34), LESTAURTINIB (168.64), CHEMBL3752910 (118.90). Authors: Glen Charles Ritschel (Ritschel Research, Tega Cay SC) and Claude (Anthropic, San Francisco CA).
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Computational Drug Repurposing for Endometriosis Using Single-Cell RNA Sequencing — Patent Specification Authors/Creators - 1. Ritschel Research - 2. Anthropic Description Patent specification for a computational drug repurposing analysis of endometriosis using single-cell RNA sequencing. Applied a standardized scRNA-seq pipeline (scVI batch correction, Leiden clustering, Wilcoxon DE, ChEMBL screening) to GSE179640 (47,957 endometrial biopsy cells, 32 samples). Identified 500 significant DE genes and scored 20,510 drug candidates; 20,117 confirmed novel via PubChem. Top candidates: CHEMBL5653589 (score 190.34), LESTAURTINIB (168.64), CHEMBL3752910 (118.90). Authors: Glen Charles Ritschel (Ritschel Research, Tega Cay SC) and Claude (Anthropic, San Francisco CA). Files Files (16.7 kB) | Name | Size | Download all | |---|---|---| | md5:3127f2d67e1e9ee0e37f9a0361c47e3d | 16.7 kB | Download | Additional details Dates - Updated - 2026-05-04v2: Corrected inventorship attribution

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endometriosis

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